Method and system for identifying homonymous points of measured objects and real image pair positions in photos

Abstract

The present invention discloses a method and system for identifying homonymous points and real image pair positions of a measured object in a photo, comprising the following steps: step 1, arranging camera array points and marker plate positions according to the characteristics of the measured object; step 2, photographing the measured object according to the arranged camera array points, and obtaining multi-angle photos with clear marker plate information; step 3, importing the photos into a computer interpretation system and performing a first photogrammetric calculation, i.e., performing rough alignment; step 4, identifying homonymous points in multiple photos and defining the real distance between the two points; the marker plate designed in the system of the present invention has the functions of color coding and defining the real distance, thereby realizing rapid identification of homonymous points in multiple photos and definition of the real distance between the two points.

Description

Technical Field

[0001] The present invention relates to the technical field of photogrammetry, and in particular to a method and system for rapidly identifying homonymous points of a measured object in multiple photos and their actual image pair positions. Background Art

[0002] Based on the principles of photogrammetry, defining points with the same name in multiple photos as control points and setting the physical distance between different control points in the real world are the basis of photogrammetry.

[0003] In daily ground feature surveying, such as the measurement of channel sections in local areas, slopes of gullies, and landmark buildings at tourist attractions, the currently available ground feature surveying technologies generally include the following:

[0004] 1. UAV-based photogrammetry technology only needs to identify control points during the interpretation process. However, the setting of control points is relatively strict and must contain absolute spatiotemporal information. The workload is large and the measurement accuracy is low (10cm level), which cannot meet the requirements of ground object measurement accuracy.

[0005] 2. When measuring ground objects, 3D laser scanning technology requires multiple measurement stations based on the shape and orientation of the object being measured. However, each station setting process is labor-intensive, tedious, and inefficient.

[0006] 3. Photogrammetry, as a new and convenient measurement method, is widely used in various research and engineering fields. It features simple control point setup, a large field of view, and efficient and high-precision measurement, with theoretical accuracy reaching millimeters. While it offers significant advantages in ground surveying, the definition of synonymous points is cumbersome and inefficient.

[0007] Therefore, the patent of this invention starts from defining the same-name points of multiple photos and setting the real distance between two points, and designs a method and system for identifying the same-name points of the measured objects in the photos and the real image pair positions. Summary of the Invention

[0008] In response to the problems in the related art, the present invention proposes a method and system for quickly identifying the same-name points of the measured object in multiple photos and their actual image pair positions, so as to realize the rapid identification of the same-name points in multiple photos and the definition of the true distance between the two points.

[0009] To achieve the above-mentioned objectives, the present invention provides the following technical solution: a method for rapidly identifying homonymous points of a measured object in multiple photos and their actual image pair positions, comprising the following steps: step 1, arranging camera array points and marker plate positions according to the characteristics of the measured object; step 2, photographing the measured object according to the arranged camera array points to obtain multi-angle photos with clear marker plate information; step 3, importing the photos into a computer interpretation system to perform a first photogrammetric calculation, i.e., rough alignment; step 4, identifying homonymous points in multiple photos and defining the true distance between the two points.

[0010] In a possible design, in step 1, it is ensured that the overlap of adjacent photos of the measured object reaches more than 60%, and each side of the signboard is clearly presented in 3 to 5 photos.

[0011] In a possible design, in step 1, there are two design schemes for the sign board. The first is a pentagonal marker, each face of the pentagon is composed of a series of circular marker blocks, the diameter of each circular marker block corresponds to a pixel value size at a different object distance, and the individual color of each circular marker block or the color combination with the surrounding marker blocks has a corresponding color code; the second is a cube marker, each face of which is composed of a number of nine-square grid marker blocks, the size of each square marker block corresponds to a pixel value size at a different object distance, and the individual color of each square marker block or the color combination with the surrounding marker blocks has a corresponding color code.

[0012] In a possible design, step 4 specifically includes step A01: determining different photos containing the same sign board according to the color code number of the sign board; step A02: then determining different photos containing the same surface of the same sign board according to the color code numbers of different surfaces of the same sign board; step A03: determining the same-name points on multiple photos according to the color code numbers and specific diameter sizes of each circular sign block; step A04: selecting the clearest 3-5 photos containing the information from the above three steps to mark the same-name points; after solving step A03, the distance between the two points of the model is the unit length in the Cartesian coordinate system. After the same-name points are identified in step A04, the real physical distance between the two same-name points in the geodetic coordinate system can be calculated according to the designed sign board size. Therefore, the real physical distance per unit length between the two points of the model can be given, realizing the definition of the real distance between the two points in the model.

[0013] In a possible design, step 4 specifically includes step B01: determining different photos containing the same signboard according to the color code number of the signboard; step B02: then determining different photos containing the same surface of the same signboard according to the color code numbers of different surfaces of the same signboard; step B03: determining the same-name points according to the color of the square sign blocks at the heart-shaped positions of each nine-square grid and the surrounding color combination; step B04: selecting the clearest 3-5 photos containing the information from the above three steps to mark the same-name points; after solving step B03, the distance between the two points of the model is the unit length in the Cartesian coordinate system. After the same-name points are identified in step B04, the real physical distance between the two same-name points in the geodetic coordinate system can be calculated according to the designed signboard size. Therefore, the real physical distance per unit length between the two points of the model can be given, thereby realizing the definition of the real distance between the two points in the model.

[0014] The present invention also provides a computer system for identifying the locations of homonymous points and real image pairs of measured objects in photos, comprising: at least one processor; and a memory, wherein the memory stores computer instructions that can be run on the processor, and when the instructions are executed by the processor, the steps of the above method are implemented.

[0015] Principle of the present invention:

[0016] The basic principle is to use two camera arrays to take pictures of the same observation area, extract the feature points of the image and match the same-name points, then calculate the three-dimensional coordinates of the same-name points through regional adjustment processing based on the camera calibration parameters, and finally interpolate and reconstruct the surface morphology of the photographed object. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A design diagram of a signboard according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of an embodiment of the present invention;

[0020] Figure 3 A diagram illustrating identification of points of the same name in multiple photos according to an embodiment of the present invention; DETAILED DESCRIPTION

[0021] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0022] In the description of the present invention, it should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for understanding and reading by those familiar with this technology, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no technical significance. Any structural modification, change in proportional relationship, or adjustment of size should still fall within the scope of the technical content disclosed in the present invention without affecting the efficacy and purpose of the present invention. At the same time, the directions or positional relationships indicated by terms such as "center", "longitudinal", "transverse", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" are based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, they should not be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium, or they can refer to internal connections between two components. A person of ordinary skill in the art can understand the specific meanings of the above terms in the present invention based on the specific circumstances. In addition, in the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0023] In at least one embodiment, Figure 1-3 As shown, the measurement method involved in the present invention has the following steps:

[0024] Step 1: Arrange the camera array points and marker plate positions according to the characteristics of the measured object, and number and mark the marker plates. Ensure that the overlap of adjacent photos of the measured object reaches more than 60%, and each side of the marker plate is clearly presented in at least three photos.

[0025] Step 2: Start photographing the measured object according to the deployed camera array points to obtain photos with clear sign information from multiple angles;

[0026] Step 3: Import the photos into the computer interpretation system and perform the first photogrammetry calculation, specifically for rough alignment;

[0027] Step 4: Quickly obtain the definition of the same-name points in multiple photos and the true distance between the two points.

[0028] The present invention also provides a computer system for identifying the locations of homonymous points and real image pairs of measured objects in photos, comprising: at least one processor; and a memory, wherein the memory stores computer instructions that can be run on the processor, and when the instructions are executed by the processor, the steps of the above method are implemented.

[0029] Size of sign board:

[0030] In the present invention, the size of a pixel is calculated by the object distance based on formula (1), and the size of each marker block on the marker plate is designed according to the actual size of the pixel corresponding to a series of object distances. Each marker block is given a different color, and different codes are designed for different color combinations to achieve the purpose of rapid recognition, accurate marking, and definition of the actual distance between two points.

[0031] Image accuracy × focal length × maximum image size = sensor width × shooting distance (1)

[0032] Among them: image accuracy - that is, resolution, meters / pixel; focal length - camera focal length 35mm; maximum image size - that is, pixels (Nikon D810 resolution is 7360×4912); sensor width - that is, image frame (Nikon D810 sensor size is 35.9×24mm); shooting distance - the maximum shooting distance of the camera in meters;

[0033] Color coding of sign boards

[0034] In the present invention, the design of the signboard mainly includes two schemes:

[0035] Solution 1: The colors mainly include red, bright green, blue, black, turquoise, yellow and pink, a total of 7 colors, starting from red and ending with pink. Considering 1 color (red, bright green, blue, etc.), 2 colors (red + bright green, red + blue, red + black, etc.), ), 3 colors (red + bright green + blue, red + bright green + turquoise, red + bright green + yellow, etc. There are a total of There are 256 combinations, namely 256 numbers, where the order of single colors is 1-7, the order of two-by-two combinations is 8-49, and the order of three-by-three combinations is 50-256 (considering the order of color combinations).

[0036] Solution 2: The colors mainly include red, bright green, blue, black, cyan, yellow and pink, a total of 7 colors, starting from red and ending with pink. Considering 1 color (red, bright green, blue, etc.), 2 colors (considering the recognition of the middle grid in the nine-square grid, the same color combination such as red + red, bright green + bright green is removed here, there are red + bright green, red + blue, red + black, etc. ), 3 colors (red + red + blue, red + bright green + turquoise, red + bright green + yellow, etc. There are a total of There are 234 combinations, namely 234 numbers, where the order of single colors is 1-7, the order of two-by-two combinations is 8-28, and the order of three-by-three combinations is 29-234 (considering the order of color combinations).

[0037] Design of sign board:

[0038] Distance range measured by Scheme 1: The pentagonal marker designed here has 7 circular markers on each surface. The diameter of each circular marker represents the size of a pixel value. Taking Nikon D810 as an example, the height of the object to be measured is 2 meters. The best viewing angle of Nikon D810 is 60°, so the closest shooting distance is 1.7 meters. Therefore, the pixel value corresponding to the closest shooting distance is the diameter of the smallest circular marker, and its corresponding diameter is 0.2mm. The diameter of the largest circular marker is 1mm, and the corresponding shooting distance is 5.5m. Therefore, high-precision measurement of objects in the range of 1.7-5.5 meters can be achieved.

[0039] Color coding design of signboards: (1) The color coding of different signboards is determined by the color combination of the top three colors of each signboard. The color codes are 50-256. Here are 11 types of signboards, which use the color combination of color code numbers 51-60 respectively;

[0040] Table 1 Color codes for different signboards

[0041]

[0042] (2) The color coding of different signboards is determined by the color combination of the lowest two layers of each surface of each signboard. The color codes are 8-49. Here, the color combination of the five surfaces of signboard No. 1 is listed, using the color combination of color codes 8-12 respectively, and each code number represents one surface;

[0043] Table 2 Color codes for different sides of signboards (for example, signboard No. 1)

[0044] Color Combinations Red+Red Red + bright green Red + Blue Red+Black Red+turquoise Color code number 8 9 10 11 12 Number on the signboard 1 2 3 4 5

[0045] (3) The color coding of the sign blocks on different sides of the sign board is determined according to the color of each circular sign block on each side of each sign board. The color codes are 1-7. Here, the color allocation of side 1 of sign board No. 1 is listed, and the colors of color codes 1-5 are used respectively.

[0046] Table 3 Color coding for different points on different sides of the signboard (Signboard No. 1, side No. 1 as an example)

[0047]

[0048]

[0049] Identification of homonymous points in multiple photos: Step 1: Determine different photos containing the same signboard according to the color code number of the signboard; Step 2: Then determine different photos containing the same surface of the same signboard according to the color code numbers of different surfaces of the same signboard; Step 3: Determine homonymous points on multiple photos according to the color code numbers and specific diameters of each circular sign block; Step 4: Select the clearest 3-5 photos containing the information from the above three steps to mark the control points. In this way, the identification of a homonymous point in multiple photos is completed, and the two-dimensional coordinates of the homonymous point are exported from the computer interpretation system. Similarly, other homonymous points are identified to generate a homonymous point file.

[0050] Definition of the true distance between two points: After the third step of solution, the system assigns the model unit length in the Cartesian coordinate system. Therefore, after completing the identification of the same-name points, the unit length between the two points is interpreted by the computer. The true distance between the two same-name points can be calculated based on the designed pentagon. The true distance between the two same-name points is imported into the adjustment calculated by the photogrammetry interpretation to complete the definition of the true distance between the two points in the fourth step.

[0051] Distance range measured by Solution 2: The cube-shaped signboard designed here consists of a number of nine-square grids, which share a heart shape. Pixels falling at any position in the nine grids use the center of the square marker block at the heart shape as the control point. Therefore, the nine-square grid can achieve combinations such as one pixel as a whole, one square marker block representing one pixel, and four square marker blocks representing one pixel. Taking Nikon D810 as an example, the height of the object to be measured is 2 meters, and the best viewing angle of Nikon D810 is 60°, so the closest shooting distance is 1.7 meters. Therefore, the pixel value corresponding to the closest shooting distance is the size of a single grid, and the corresponding setting of a grid size is 0.2mm, which can achieve shooting in the range of 1.7-5 meters and high-precision control point recognition.

[0052] Color coding design of signboards: (1) The color coding of different signboards is determined by the color combination of the top square sign blocks (3 in a group) of each signboard. The color codes are 29-234. Here are 11 types of signboards, which use the color combination of color code numbers 29-39 respectively;

[0053] Table 4 Color codes for different signboards

[0054]

[0055]

[0056] (2) The color coding on different signboards is determined by the two color combinations of the nine-square grid in the lower right corner of each face of each signboard. The color codes are 8-28. Here, the color combinations of the five faces of signboard No. 1 are listed, using the color combinations of color codes 8-12 respectively, and each code number represents one face;

[0057] Table 5 Color codes for different sides of signboards (for example, signboard No. 1)

[0058]

[0059] (3) The color coding of the sign blocks on different sides of the sign board is determined by the color of the square sign blocks at the heart-shaped positions of the nine-square grid on each side of each sign board and the surrounding color combination. The color codes are 1-7. Here, the color distribution of side 1 of sign board No. 1 is listed, using the colors of color codes 1-7 respectively.

[0060] Table 6 Color coding for different points on different sides of the signboard (Signboard No. 1, side No. 1 as an example)

[0061] Color Type bright green blue black red bright green blue blue Pink bright green Color Coding 2 3 4 1 2 3 3 7 2

[0062] Identification of homonymous points in multiple photos and definition of the distance between two points: Step 1, determine different photos containing the same signboard according to the color code number of the signboard; Step 2, determine different photos containing the same surface of the same signboard according to the color code numbers of different surfaces of the same signboard; Step 3, determine homonymous points according to the color of the square sign blocks at the heart shape of each nine-square grid and the surrounding color combination; Step 4, select the clearest 3-5 photos containing the information from the above three steps to mark the control points, thus completing the identification of a homonymous point in multiple photos, and deriving the two-dimensional coordinates of the homonymous point from the computer interpretation system. Similarly, identify other homonymous points and generate a homonymous point file.

[0063] Definition of the true distance between two points: After the third step of solution, the system assigns the model unit length in the Cartesian coordinate system. Therefore, after completing the identification of the same-name points, the unit length between the two points is interpreted by the computer. The true distance between the two same-name points can be calculated based on the designed pentagon. The true distance between the two same-name points is imported into the adjustment calculated by the photogrammetry interpretation to complete the definition of the true distance between the two points in the fourth step.

[0064] Step 5: Import the information obtained in step 4 into the adjustment calculation file of the photogrammetric interpretation calculation, and perform a second photogrammetric calculation to achieve the overall accuracy and dimensional precision of the measured object under the relative coordinate interpretation.

[0065] Although the above methods are illustrated and described as a series of acts for simplicity of explanation, it is to be understood and appreciated that these methods are not limited by the order of the acts, as some acts may occur in a different order and / or concurrently with other acts from those illustrated and described herein or not illustrated and described herein but understandable to those skilled in the art according to one or more embodiments.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying the locations of homonymous points and real image pairs of measured objects in a photograph, characterized in that: The method comprises the following steps: step 1, arranging the points of the camera array and the position of the marker plate according to the characteristics of the object to be measured; in step 1, there are two design schemes for the marker plate, the first is a pentagonal marker, each face of the pentagon is composed of a series of circular marker blocks, the diameter of each circular marker block corresponds to a pixel value size of a different object distance, and the individual color of each circular marker block or the color combination with the surrounding marker blocks has a corresponding color code; the second is a cube marker, each face of which is composed of a number of nine-square grid-shaped marker blocks, the size of each square marker block corresponds to a pixel value size of a different object distance, and the individual color of each square marker block or the color combination with the surrounding marker blocks has a corresponding color code; Step 2: Photograph the object to be measured according to the deployed camera array points to obtain multi-angle photos with clear sign information; Step 3: Import the photos into the computer interpretation system to perform the first photogrammetric calculation, that is, rough alignment; Step 4: Identify the same-name points in multiple photos and define the true distance between the two points.

2. The method of identifying the locations of the same-name points and real image pairs of the measured objects in a photograph according to claim 1, characterized in that: In step 1, it is ensured that the overlap of adjacent photos of the measured object reaches more than 60%, and each surface of the sign board is clearly presented in 3 to 5 photos.

3. The method of identifying the locations of the same-name points and real image pairs of the measured objects in a photograph according to claim 1, characterized in that: Step 4 specifically includes step A01: determining different photos containing the same sign board according to the color code number of the sign board; step A02: then determining different photos containing the same surface of the same sign board according to the color code numbers of different surfaces of the same sign board; step A03: determining the same-name points on multiple photos according to the color code numbers and specific diameter sizes of each circular sign block; step A04: selecting the clearest 3-5 photos containing the information of the above three steps to mark the same-name points; after solving step A03, the distance between the two points of the model is the unit length in the Cartesian coordinate system. After the same-name points are identified in step A04, the real physical distance between the two same-name points in the geodetic coordinate system can be calculated according to the designed sign board size. Therefore, the real physical distance per unit length between the two points of the model can be given, realizing the definition of the real distance between the two points in the model.

4. The method of identifying the locations of the same-name points and real image pairs of the measured objects in a photograph according to claim 1, characterized in that: Step 4 specifically includes step B01: determining different photos containing the same signboard according to the color code number of the signboard; step B02: then determining different photos containing the same surface of the same signboard according to the color code numbers of different surfaces of the same signboard; step B03: determining the same-name points according to the color of the square sign blocks at the heart-shaped position of each nine-square grid and the surrounding color combination; step B04: selecting the clearest 3-5 photos containing the information of the above three steps to mark the same-name points; after solving step B03, the distance between the two points of the model is the unit length in the Cartesian coordinate system. After the same-name points are identified in step B04, the real physical distance between the two same-name points in the geodetic coordinate system can be calculated according to the designed signboard size. Therefore, the real physical distance per unit length between the two points of the model can be given, realizing the definition of the real distance between the two points in the model.

5. A computer system for identifying the locations of homonymous points and real image pairs of measured objects in a photograph, characterized in that: include: at least one processor; and a memory storing computer instructions executable on the processor, wherein the instructions, when executed by the processor, implement the steps of the method according to any one of claims 1 to 4.

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